Harnessing Deepfake Image Detection with Artificial Intelligence Techniques

Deepfake technology poses significant risks to digital security and misinformation. This study presents a deepfake detection system using advanced deep learning models, including CNNs, ResNet50V2, and Vision Transformers, enhanced with ensemble learning for improved accuracy. The proposed model achieves high precision and generalizability across multiple datasets. All datasets were obtained from Kaggle, adhering to ethical guidelines, with no personally identifiable information collected. The system ensures data security and compliance with licensing terms. Experimental results show improved detection accuracy while maintaining computational efficiency. This research contributes to AI-driven media forensics by providing a scalable solution for deepfake identification.